32 research outputs found

    Genetic Variation in Selenoprotein Genes, Lifestyle, and Risk of Colon and Rectal Cancer

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    BACKGROUND: Associations between selenium and cancer have directed attention to role of selenoproteins in the carcinogenic process. METHODS: We used data from two population-based case-control studies of colon (n = 1555 cases, 1956 controls) and rectal (n = 754 cases, 959 controls) cancer. We evaluated the association between genetic variation in TXNRD1, TXNRD2, TXNRD3, C11orf31 (SelH), SelW, SelN1, SelS, SepX, and SeP15 with colorectal cancer risk. RESULTS: After adjustment for multiple comparisons, several associations were observed. Two SNPs in TXNRD3 were associated with rectal cancer (rs11718498 dominant OR 1.42 95% CI 1.16,1.74 pACT 0.0036 and rs9637365 recessive 0.70 95% CI 0.55,0.90 pACT 0.0208). Four SNPs in SepN1 were associated with rectal cancer (rs11247735 recessive OR 1.30 95% CI 1.04,1.63 pACT 0.0410; rs2072749 GGvsAA OR 0.53 95% CI 0.36,0.80 pACT 0.0159; rs4659382 recessive OR 0.58 95% CI 0.39,0.86 pACT 0.0247; rs718391 dominant OR 0.76 95% CI 0.62,0.94 pACT 0.0300). Interaction between these genes and exposures that could influence these genes showed numerous significant associations after adjustment for multiple comparisons. Two SNPs in TXNRD1 and four SNPs in TXNRD2 interacted with aspirin/NSAID to influence colon cancer; one SNP in TXNRD1, two SNPs in TXNRD2, and one SNP in TXNRD3 interacted with aspirin/NSAIDs to influence rectal cancer. Five SNPs in TXNRD2 and one in SelS, SeP15, and SelW1 interacted with estrogen to modify colon cancer risk; one SNP in SelW1 interacted with estrogen to alter rectal cancer risk. Several SNPs in this candidate pathway influenced survival after diagnosis with colon cancer (SeP15 and SepX1 increased HRR) and rectal cancer (SepX1 increased HRR). CONCLUSIONS: Findings support an association between selenoprotein genes and colon and rectal cancer development and survival after diagnosis. Given the interactions observed, it is likely that the impact of cancer susceptibility from genotype is modified by lifestyle

    A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

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    A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science
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